Businesses which have equipment therein typically have a maintenance schedule for maintaining the equipment. For some businesses, the maintenance schedule is virtually non-existent; equipment is maintained or fixed only when it fails in some way. When a critical machine fails in such a factory, the entire production process may come to a stop.
Some businesses solve this problem by performing preventive maintenance wherein they replace parts of machines at certain, predetermined intervals, whether or not the parts are close to failing. This avoids many failures. However, perfectly good parts are often unnecessarily replaced.
Other businesses have computerized their maintenance systems by using sensors, connected to computers, to measure the operation of their machines. The computers typically alert the maintenance personnel when the sensors detect a failure of some part of the machine.
Although the computerized systems detect where failures occur, easing the job of repairing the failure, the computerized systems do not generally provide a lot of warning that a failure is about to occur.
Device monitoring systems, using single or multiple sensors, are known, some of which are described in the article, "Empirical Models for Intelligent Data Validation" produced by Halliburton NUS Environmental Corporation of Idaho Falls, Id., U.S.A. The systems described in the article use reference data, collected when the device being monitored was operating as desired, to define a model of "normal device behavior". Later output data, as a result of later input signals, are compared to model output produced from the same input signals and an alert is provided if the model output does not match the real output data.